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A model of saliency-based visual attention for rapid scene analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence · 1998 · Vol. 20(11) · pp. 1254–1259

Laurent Itti✉(California Institute of Technology)Christof Koch(California Institute of Technology)Ernst Niebur(Kennedy Krieger Institute)

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Abstract

A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing saliency. The system breaks down the complex problem of scene understanding by rapidly selecting, in a computationally efficient manner, conspicuous locations to be analyzed in detail.

Visual Attention and Saliency Detection Visual perception and processing mechanisms Neural dynamics and brain functionArtificial intelligenceComputer scienceComputer visionVisual attentionVisualizationPattern recognition (psychology)Image (mathematics)Human visual system modelSaliency mapArtificial neural network

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